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Record W6962538780 · doi:10.17026/ar/nrfzkp

Landschapskaarten naar periode en diepte voor archeologisch gebruik in Holoceen-afgedekte delen van Nederland

2024· dataset· nl· W6962538780 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueDANS Data Station Archaeology · 2024
Typedataset
Languagenl
FieldEnvironmental Science
TopicEnvironmental Conservation and Management
Canadian institutionsnot available
Fundersnot available
KeywordsPilgrimQuarter (Canadian coin)

Abstract

fetched live from OpenAlex

Dit is een actualisatie (V2; productie 2020-2021) van een landelijk dekkend digitaal kaartbestand (T0123.shp) van Holocene begraven landschappen, voor gebruik door archeologische professionals. De eerdere versie (V1; productie 2014-2017) functioneerde sinds 2018 in RCE-data portalen (Rijksdienst Cultureel Erfgoed; Bronnen en Kaarten: Kaart-viewer: <a href="https://rce.webgis.nl/nl/map/begraven-landschappen">Buried Landscapes</a>; Thematische viewer <a href="https://lil.rce.rnatoolset.net">Landgebruik in Lagen</a>).<br><br> De kartering bestrijkt vier archeologisch relevante tijdsneden (T0 t/m T3; samen 12,000 voor Chr. tot 900 na Chr. bestrijkend): vier perioden van natuurlijke landschapsontwikkeling tot aan de grootschalige ontginningen van de kustvlakte (voor het landschap uit die jongste 1100 jaar wordt op RCE's Archeologische Landschappenkaart aangesloten, die in 2019 was herzien). De kartering verwerkte daartoe bestaande digitale geologische kaartbestanden zoals die door de partijen Universiteit Utrecht (UU), TNO en Deltares zijn aangelegd en worden onderhouden. De in 2014-2017 ontwikkelde geautomatiseerde wijze van productie is in 2020-2021 andermaal doorlopen, met geactualiseerde uitgangs-bestanden. <br><br> Net als bij V1 (2017), bevat de dataset bevat de GIS Begraven Landschappenkaart als GIS bestanden (digitaal eindproduct), het geactualiseerde vervaardigingsrapport (Cohen & Pierik 2021) en kopieën van de uitgangs-bestanden (digitaal bron-materiaal, geactualiseerd 2016-2021), en bestanden die de gevolgde workflow digitaal vastlegden (ArcGIS ToolSet.MBX met data-combinatie modellen: scripted-workflow). De legenda-opzet is ongewijzigd t.o.v. van V1 (Zie Cohen 2017 in de V1 dataset). De gebiedsindeling is zeewaarts (12-mijlszone; memo Hijma en Van Onselen 2021) en landinwaarts (Holoceen Maasdal Limburg) uitgebreid. Anders dan in V1 werden de paleo-hoogtebestanden niet geactualiseerd.<br><br> ==<br><br> This dataset is an actualisation (V2; produced 2020-2021) of a digital map (T0123.shp) of national coverage on Holocene Buried Landscapes, for use by archaeological professionals. The previous version (V1; produced 2014-2017) functioned since 2018 in The Netherlands' cultural heritage agency (RCE) data portals (<a href="https://www.cultureelerfgoed.nl">www.cultureelerfgoed.nl</a> section <a href="https://www.cultureelerfgoed.nl/onderwerpen/bronnen-en-kaarten">Bronnen en Kaarten</a>; Map viewer: <a href="https://rce.webgis.nl/nl/map/begraven-landschappen">Buried Landscapes</a>; Thematic viewer<a href="https://lil.rce.rnatoolset.net">Landgebruik in Lagen</a>).<br><br> The map products cover four time slices, following an archaeological division scheme (T0 t/m T3; together stretching 12,000 BCE to 900 CE). They cover natural landscape evolution up to Medieval phases of extensive coastal and delta plain reclamation and reorganization (the landscape resulting from the last 1100 years is mapped as part of RCE's Archeologische Landschappenkaart, actualised in 2019). The mapping made use of existing digital geological dataset as maintained at Utrecht University (UU), TNO - Geological Survey of the Netherlands (TNO-GDN), and Deltares. An automated production method (developed in 2014-2017) was reran, taking in updated source mapping products.<br><br> The data set contains the GIS data that stores the maps (the end product), an actualised version of the documentation of the production work flow (PDF 01 Cohen & Pierik 2021), copies of the ruling versions of the input digital map data (source data, actualised 2016-2021), and files that store the work flow digitally (ArcGIS ToolSet.MBX with processing-models: the scripted workflow). The legend setup is unchanged to that of V1 (03_Cohen 2017 and 05_Cohen et al. 2017 in there). Extent and areal partitioning of the study area was enlarged in seawards (12-mile territorial waters; PDF 03 memo Hijma en Van Onselen 2021) and landwards (Holocene Meuse valley Limburg).<br><br>

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.066
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0030.009
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.040

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.026
GPT teacher head0.284
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it